I think Lisp still has an edge for larger projects and for applications where the speed of the compiled code is important. But Python has the edge (with a large number of students) when the main goal is communication, not programming per se. In terms of programming-in-the-large, at Google and elsewhere, I think that language choice is not as important as all the other choices: if you have the right overall architecture, the right team of programmers, the right development process that allows for rapid development with continuous improvement, then many languages will work for you; if you don't have those things you're in trouble regardless of your language choice.
Although to be honest, there's Clojure, which isn't as easy to learn as Python nor as flexible/powerful as CL, but sits in confortable middle ground.
Not pure, not perfect, but still great!
It's elegant learn programming, history of AI, and simple old school Common Lisp in the same package.
AI methods include GPS, Eliza style chatbots, symbolic math, constraint satisfaction, logic programming, natural language programming.
It's a wonderful book and it even includes some advanced advice on how to speedup Common Lisp code, which I have not found elsewhere!
I think the course to which you refer is on Udacity, with Thrun; I found it easier to read the book.